Smart Labeling


Machine learning assistance to accelerate ROI on your AI initiatives




Our Smart Labeling capabilities have built-in Machine Learning assistance to save customers time, effort and money - delivering hight-quality training data and accelerating the ROI and your AI initiatives.

Ensuring you have enough labeled data to adequately train your models is no easy feat. Each model may need hundreds of thousands, if not millions of rows of labeled training data from which to lean. Collecting and annotating that amount of high-quality data consumes a lot of time and resources - especially if you’re relying on the power of human annotations alone.

That’s why our industry leading data annotation platform has Smart Labeling. This suite of innovative capabilities uses Machine Learning assistance in the data annotation process to automate and improve productivity, quality, and delivery of your data collection and data annotation projects.


Image Image




Image

Appen Smart Labeling Focuses
on Three Specific Areas



Machine Learning can drive quality, cost and time saving in the data annotation process:



Pre-Labeling


Machine Learning provides an initial 'best guess' hypothesis before contributors start the task. With human contributors reviewing pre-processed annotations instead of starting a judgment from scratch, the time needed to annotate data drastically reduces.


Speed Labeling


Machine Learning provides for in-tool efficiency, quality and accuracy improving ergonomic conditions while contributors work. This reduces cognitive strain and allows contributors to work faster and more comfortable, increasing throughput of their annotations.


Smart Validators


Our Machine Learning models verify human judgments before they are finalized. This ensures you are only paying for quality judgements, eliminating the need for peer reviews and the risk you’re paying for judgements that don’t fit your requirements.






Customers Running World-Class AI


Image
Image
Image
Image
Image
Image
Image

Learn More




Image

Smart Labeling Capabilities
our Customers Enjoy


Image

Pre-Labeling for Autonomous Vehicle Image Pixel Labeling


Images are automatically applied with Pixel Labeled classes based on the ontologies you choose. They are then reviewed by a contributor to ensure the annotations are correct and to your specifications. Our statistically significant A/B tests show Pre-Labeling PLSS can improve contributor productivity by 91.5% without quality compromise.
Image

Video Annotation with Speed Labeling


Videos are split into frame-by-frame sequences. Contributors label each object in the first frame, then Speed Labeling tracks and predicts object locations in subsequent frames for the remaining frames. Contributors can then supervise and correct as needed. This results in annotation speeds up to 100x faster than using human annotations alone.
Image

Image Transcription with Speed Labeling


Contributors box text in an image and then OCR assistance predicts transcribed text for each box. Contributors can adjust text as needed. Output includes whether the transcription was provided by the model or by the contributor. Speed Labeling increases efficiency by 33%.
Image

Text Utterance Collection with Smart Validators


Utterances are checked against three validators (duplicate detection, coherence detection and language detection) before being eligible for submission. This tool is commonly used to train chatbots, resulting in up to a 35% reduction in error rates using real time models.